Identification of a disulfidptosis-related lncRNA signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma.

PURPOSE: Disulfidptosis, a newly identified form of cell death, is triggered by disulfide stress. Herein, a unique signature was developed based on disulfidptosis-related lncRNAs (DRlncRNAs) for the prognostic and immune landscape prediction of head and neck squamous cell carcinoma (HNSCC). METHODS: Transcriptome, somatic mutation, and clinical data were acquired at The Cancer Genome Atlas database. Individuals were partitioned into training and test cohorts at a 1:1 ratio to facilitate the development of a DRlncRNA signature using the least absolute shrinkage and selection operation method. Based on the median risk score, all HNSCC individuals were stratified into the high-risk group (HRG) and low-risk group (LRG). Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were used to estimate the prognostic value, and a nomogram was generated for survival prediction. To provide a more comprehensive assessment, the tumor microenvironment, functional enrichment, immune cell infiltration, and immunotherapeutic sensitivity were explored between LRG and HRG. RESULTS: A DRlncRNA signature was established with 10 DRlncRNAs. The corresponding values of areas under the ROC curves for 1-, 3-, and 5-year overall survival were 0.710, 0.692, and 0.640. A more favorable prognosis was noted in the patients with lower risk, along with higher immune scores, increased immune-related functions, and immune cell infiltration, as well as improved response to the immunotherapeutic intervention in comparison with individuals at higher risk. CONCLUSION: These findings demonstrate that the developed DRlncRNA signature holds promise as a reliable prognostic marker and predictor of immunotherapy response in HNSCC patients.

SLC20A1 is a prospective prognostic and therapy response predictive biomarker in head and neck squamous cell carcinoma.

BACKGROUND: SLC20A1, a prominent biomarker in several cancers, has been understudied in its predictive role in head and neck squamous cell carcinoma (HNSCC). METHODS: The Cancer Genome Atlas (TCGA) database was used to analyze HNSCC prognosis, SLC20A1 overexpression, and clinical characteristics. Quantitative real-time PCR and Western blot analysis confirmed SLC20A1 expression in HNSCC tissues. Cellular behaviors such as invasion, migration and proliferation were assessed using Transwell, wound healing and colony formation assays. Immune system data were obtained from the Tumor Immune Estimation Resource (TIMER) and CIBERSORT databases. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore biological parameters and pathways associated with SLC20A1 overexpression in HNSCC. RESULTS: In 499 HNSCC samples, SLC20A1 mRNA and protein expression were significantly higher than in 44 normal counterparts, confirmed by 24 paired samples. Patients were categorized based on SLC20A1 levels, survival status and overall survival. High SLC20A1 expression correlated with advanced T stage, increased risk scores and decreased survival. Stage, age and SLC20A1 expression emerged as independent predictive factors for HNSCC in univariate and multivariate analyses. SLC20A1 overexpression, which is associated with poor prognosis, may influence cell proliferation, migration, invasion, chemotherapy response, and the immune milieu. CONCLUSIONS: SLC20A1 overexpression in HNSCC, characterized by increased cellular invasion, migration and proliferation, is a potential prognostic biomarker and therapeutic response indicator.

Development of Chromatin Regulator-related Molecular Subtypes and a Signature to Predict Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Chromatin regulators (CRs) serve as indispensable factors in tumor biological processes by influencing tumorigenesis and the immune microenvironment and have been identified in head and neck squamous cell carcinoma (HNSCC). Hence, CR-related genes (CRRGs) are considered potential biomarkers for predicting prognosis and immune infiltration in HNSCC. In this study, we established a novel signature for predicting the prognosis and immunotherapeutic response of HSNCC. METHODS: A total of 870 CRRGs were obtained according to previous studies. Subsequently, patients in the TCGA-HNSC cohort were divided into different clusters based on the expression of prognostic CRRGs. Kaplan‒Meier (K‒M) survival analysis was conducted to compare the prognosis in clusters, and the CIBERSORT and ssGSEA methods assessed the immune infiltration status. In addition, the differences in immunotherapeutic responses were determined based on the TICA database. Furthermore, the differentially expressed CRRGs between clusters were identified, and the predictive signature was established according to the results of univariate Cox, least absolute shrinkage and selection operator regression analysis, and multivariate Cox. The predictive effects of the risk model were evaluated according to the area under the receiver operating characteristic (ROC) curve (AUC) in both the training and external test cohorts. A nomogram was established, and survival comparisons, functional enrichment analyses, and immune infiltration status and clinical treatment assessments were performed. In addition, the hub gene network and related analysis were conducted with the Cytohubba application. RESULTS: Based on the expression of prognostic CRRGs, patients were divided into two clusters, in which Cluster 1 exhibited a better prognosis, more enriched immune infiltration, and a better immunotherapeutic response but exhibited chemotherapy sensitivity. The AUC values of the 1-, 3- and 5- year ROC curves for the risk model were 0.673, 0.732, and 0.692, respectively, as well as 0.645, 0.608, and 0.623 for the test set. In addition, patients in the low-risk group exhibited more immune cell enrichment and immune function activation, as well as a better immunotherapy response. The hub gene network indicated ACTN2 as the core gene differentially expressed between the two risk groups. CONCLUSIONS: We identified molecular subtypes and established a novel predictive signature based on CRRGs. This effective CRRS system can possibly provide a novel research direction for exploring the correlation between CRs and HNSCC and requires further experimental validation.

Predicting the prognosis, immune response, and immunotherapy in head and neck squamous cell carcinoma using a novel risk model based on anoikis-related lncRNAs.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is an extremely heterogeneous and metastatic disease. Anoikis, which is a specific type of programmed apoptosis, is involved in tumor metastasis, tissue homeostasis, and development. Herein, we constructed an anoikis-related long non-coding RNA (lncRNA) signature to predict the prognosis, immune responses, and therapeutic effects in HNSCC patients. METHODS: A total of 501 HNSCC samples were acquired from the TCGA database and randomly classified into the training and validation groups (1:1 ratio). Thereafter, the results derived from the training set were analyzed with the LASSO regression analysis, and a novel anoikis-related lncRNA risk model was constructed. Time-dependent ROC curves and Kaplan-Meier analysis were carried out to assess the diagnostic value and survival outcomes. A nomogram was utilized to predict the prognostic accuracy. Furthermore, we studied the tumor microenvironment, tumor mutation burden, enrichment pathways, and the response to chemotherapy and immunotherapy. RESULTS: Seven anoikis-related lncRNAs (AC015878.1, CYTOR, EMSLR, LINC01503, LINC02084, RAB11B-AS1, Z97200.1) were screened to design a novel risk model, which was recognized as the independent prognostic factor for HNSCC patients. The findings implied that low-risk patients showed significantly longer OS, PFS, and DSS compared to those high-risk patients. The two groups that were classified using the risk model showed significant differences in their immune landscape. The risk model also predicted that low-risk HNSCC patients could attain a better response to immunotherapy, while high-risk patients would be more sensitive to gemcitabine, docetaxel, and cisplatin. CONCLUSIONS: We constructed a novel risk model that could be employed for effectively predicting patient prognosis with a good independent prognostic value for HNSCC patients. Furthermore, this model could be used for designing new immunotherapeutic and chemotherapeutic strategies, and it helps clinicians establish personalized and detailed strategies for HNSCC patients.

Identification and validation of a novel signature based on T cell marker genes to predict prognosis, immunotherapy response and chemotherapy sensitivity in head and neck squamous carcinoma by integrated analysis of single-cell and bulk RNA-sequencing.

T cells are among the most potent anti-tumor cells that are found in humans. Our study sought to develop a reliable signature incorporating T cell marker genes (TMGs) for predicting the prognosis and therapy responsiveness of head and neck squamous cell carcinoma (HNSCC) patients. We downloaded scRNA-seq data from the GSE181919 to identify TMGs. Subsequently, we devised a 12 TMG signature in the TCGA HNSCC cohort by using LASSO analysis. Patients with high-risk scores were shown to experience unfavorable progression-free survival, disease-specific survival, and overall survival, which was validated in the GSE65858 cohort. Additionally, the nomogram integrated risk score and clinical features are more suitable for clinical application. The enrichment analyses of both pathways and functions showed that high- and low-risk patients had functionally related distinctions. Furthermore, analysis of the immunological landscape confirmed that the low-risk patients had a larger percentage of infiltrating immune cells as well as a higher incidence rate of immune-related events. In the meantime, a greater IPS score and expression of immune checkpoint genes suggested significantly favorable responsiveness to immunotherapy in low-risk patients. On the other hand, the high-risk patients had a greater degree of sensitivity to the chemotherapy agents, which included paclitaxel, gemcitabine, docetaxel, and cisplatin. Our finding revealed that this TMG signature independently functioned as a prognostic marker and guided individualized immunotherapy and chemotherapy selection for patients with HNSCC.

Identification of a new anoikis-related gene signature for prognostic significance in head and neck squamous carcinomas.

Anoikis, a mode of programmed cell death, is essential for normal development and homeostasis in the organism and plays an important role in the onset and progression of cancers. The authors of this research sought to establish a gene signature associated with anoikis to predict therapy outcomes and patient prognosis for individuals with head and neck squamous cell carcinoma (HNSCC). Transcriptome data of anoikis-related genes (ARGs) in individuals with HNSCC were retrieved from public databases to aid in the formulation of the gene signature. A novel ARG signature was then created using a combination of the Least Absolute Shrinkage and Selection Operator regression and Cox regression analysis. The relationship between ARGs and tumor immune microenvironment in HNSCC was explored using single-cell analysis. HNSCC individuals were classified into high-risk and low-risk groups as per the median value of risk score. The study also investigated the variations in the infiltration status of immune cells, tumor microenvironment, sensitivity to immunotherapy and chemotherapeutics, as well as functional enrichment between the low-risk and high-risk categories. A total of 18 ARGs were incorporated in the formulation of the signature. Our signature's validity as a standalone predictive predictor was validated by multivariate Cox regression analysis and Kaplan-Meier survival analysis. Generally, the prognosis was worse for high-risk individuals. Subjects in the low-risk groups had a better prognosis and responded in a better way to combination immunotherapy, had higher immunological ratings and activity levels, and had more immune cell infiltration. In addition, gene set enrichment analysis findings showed that the low-risk subjects exhibited heightened activity in several immune-related pathways. However, the high-risk patients responded better to chemotherapy. The aim of this research was to develop a new ARG signature to predict the prognosis and sensitivity to immunotherapeutic and chemotherapeutic schemes for HNSCC patient. As a result, this could help spur the creation of new chemotherapeutics and immunotherapeutic approaches for patients with HNSCC.

5-Methylcytosine-related lncRNAs: predicting prognosis and identifying hot and cold tumor subtypes in head and neck squamous cell carcinoma.

BACKGROUND: 5-Methylcytosine (m5C) methylation is recognized as an mRNA modification that participates in biological progression by regulating related lncRNAs. In this research, we explored the relationship between m5C-related lncRNAs (mrlncRNAs) and head and neck squamous cell carcinoma (HNSCC) to establish a predictive model. METHODS: RNA sequencing and related information were obtained from the TCGA database, and patients were divided into two sets to establish and verify the risk model while identifying prognostic mrlncRNAs. Areas under the ROC curves were assessed to evaluate the predictive effectiveness, and a predictive nomogram was constructed for further prediction. Subsequently, the tumor mutation burden (TMB), stemness, functional enrichment analysis, tumor microenvironment, and immunotherapeutic and chemotherapeutic responses were also assessed based on this novel risk model. Moreover, patients were regrouped into subtypes according to the expression of model mrlncRNAs. RESULTS: Assessed by the predictive risk model, patients were distinguished into the low-MLRS and high-MLRS groups, showing satisfactory predictive effects with AUCs of 0.673, 0.712, and 0.681 for the ROCs, respectively. Patients in the low-MLRS groups exhibited better survival status, lower mutated frequency, and lower stemness but were more sensitive to immunotherapeutic response, whereas the high-MLRS group appeared to have higher sensitivity to chemotherapy. Subsequently, patients were regrouped into two clusters: cluster 1 displayed immunosuppressive status, but cluster 2 behaved as a hot tumor with a better immunotherapeutic response. CONCLUSIONS: Referring to the above results, we established a m5C-related lncRNA model to evaluate the prognosis, TME, TMB, and clinical treatments for HNSCC patients. This novel assessment system is able to precisely predict the patients' prognosis and identify hot and cold tumor subtypes clearly for HNSCC patients, providing ideas for clinical treatment.

High eukaryotic initiation factor 5A2 expression predicts poor prognosis and may participate in the SNHG16/miR-10b-5p/EIF5A2 regulatory axis in head and neck squamous cell carcinoma.

BACKGROUND: This study attempted to investigate the significance of eukaryotic initiation factor 5A2 (EIF5A2) in the prognosis and regulatory network of head and neck squamous cell carcinoma (HNSCC). METHODS: EIF5A2 expression, prognostic information, and methylation levels of HNSCC were collected from the Cancer Genome Atlas (TCGA) database. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot analyses were performed to determine EIF5A2 levels in HNSCC and normal tissue samples. R software was employed for expression analysis and prognosis assessment of EIF5A2 in HNSCC. A competing endogenous RNA (ceRNA) network was generated with the starBase database. Gene set enrichment analysis (GSEA) was used to determine the enriched physiological functions and network related to high expression of EIF5A2 in HNSCC. Immune infiltration-related outcomes were acquired from the CIBERSORT and Tumor Immune Estimation Resource (TIMER) database. RESULTS: EIF5A2 overexpression was observed in HNSCC and linked to poor progression-free survival and overall survival time. Cox regression analyses showed that EIF5A2 level was a stand-alone indicator of HNSCC patients' prognosis. A ceRNA network analysis highlighted the SNHG16/miR-10b-5p/EIF5A2 axis in EIF5A2 regulation. The GSEA results indicated that EIF5A2 was involved in complex signaling pathways. The CIBERSORT and TIMER databases revealed significant associations between EIF5A2 expression and immune cell infiltration. CONCLUSION: EIF5A2 overexpression may be a risk factor for prognosis in HNSCC and may be regulated by the SNHG16/miR-10b-5p/EIF5A2 axis.

Pancancer analysis reveals the role of disulfidptosis in predicting prognosis, immune infiltration and immunotherapy response in tumors.

Disulfidptosis has been reported as a novel cell death process, suggesting a therapeutic strategy for cancer treatment. Herein, we constructed a multiomics data analysis to reveal the effects of disulfidptosis in tumors. Data for 33 kinds of tumors were downloaded from UCSC Xene, and disulfidptosis-related genes (DRGs) were selected from a previous study. After finishing processing data by the R packages, the expression and coexpression of DRGs in different tumors were assessed as well as copy number variations. The interaction network was drawn by STRING, and the activity of disulfidptosis was compared to the single-sample gene set enrichment analysis algorithm. Subsequently, the differences in DRGs for prognosis and clinicopathological features were evaluated, and the tumor immune microenvironment was assessed by the TIMER and TISCH databases. Tumor mutation burden, stem cell features and microsatellite instability were applied to predict drug resistance, and the expression of checkpoints was identified for the prediction of immunotherapy. Moreover, the TCIA, CellMiner and Enrichr databases were also utilized for selecting potential agents. Ten DRGs were differentially expressed in tumors, and the plots of coexpression and interaction revealed their correlation. Survival analysis suggested SLC7A11 as the most prognosis-related DRG with the most significant results. Additionally, the comparison also reflected the differences in DRGs in the status of pathologic lymph node metastasis for 5 types of tumors. The tumor immune microenvironment showed commonality among tumors based on immune infiltration and single-cell sequencing, and the analysis of tumor mutation burden, stemness and microsatellite instability showed a mostly positive correlation with DRGs. Moreover, referring to the prediction about clinical treatment, most DRGs can enhance sensitivity to chemotherapeutic agents but decrease the response to immune inhibitors with increasing expression. In this study, a primarily synthetic landscape of disulfidptosis in tumors was established and provided guidance for further exploration and investigation.

Identification of a cuproptosis-related lncRNA signature to predict the prognosis and immune landscape of head and neck squamous cell carcinoma.

Background: Cuproptosis is considered a novel copper-induced cell death model regulated by targeting lipoylated TCA cycle proteins. In this study, we established a novel signature based on cuproptosis-related lncRNAs (crlncRNAs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma. Methods: RNA-seq matrix, somatic mutation files, and clinical data were obtained from The Cancer Genome Atlas database. After dividing patients into two sets, a crlncRNA signature was established based on survival related crlncRNAs, which were selected by the univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. To evaluate the model, Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) were utilized, and a nomogram was established for survival prediction. Immune landscape analysis, drug sensitivity, cluster analysis, tumor mutation burden (TMB) and ceRNA network analysis were conducted subsequently. Results: A crlncRNA related prognosis signature was finally constructed with 12 crlncRNAs. The areas under the ROC curves (AUCs) were 0.719, 0.705 and 0.693 respectively for 1, 3, and 5-year's overall survival (OS). Patients in the low-risk group behaved a better prognosis, lower TMB, higher immune function activity and scores. In addition, patients from cluster 2 were more sensitive to chemotherapy and immunotherapy. Conclusion: In this study, we constructed a novel crlncRNA risk model to predict the survival of HNSCC patients. This reliable and acceptable prognostic signature may guide and promote the progress of novel treatment strategies for HNSCC patients.

Identification of cuproptosis-related subtypes and characterization of the tumor microenvironment landscape in head and neck squamous cell carcinoma.

BACKGROUND: Cuproptosis is considered a novel copper-dependent cell death model. In this study, we established a novel scoring system based on 10 cuproptosis-related genes (CRGs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC). METHODS: The RNA-seq data of HNSCC patients were downloaded from the GEO and TCGA databases and were merged into a novel HNSCC cohort. Multiomics landscape analyses were conducted, including tumor mutation burden (TMB), copy number variations and the interaction network of CRGs. Patients were then divided into different cuproptosis subtypes based on the expression of 10 CRGs and subsequently regrouped into novel gene clusters referring to differentially expressed genes. A cuproptosis score (CS) system was established using principal component analysis. The CIBERSORT, ssGSEA and ESTIMATE algorithms were used to assess the tumor immune microenvironment. Moreover, the immunotherapeutic and chemotherapeutic responses were assessed. RESULTS: Patients were divided into three cuproptosis subtypes and subsequently regrouped into three gene clusters, reflecting different immune infiltration. Assessed by the CS system, those with higher CSs exhibited worse prognosis and higher TMB frequency. Nevertheless, the immune-related analysis revealed patients in the low-CS group appeared immunosuppressive and easily suffered from immune escape. High CSs possibly show high expression of immune checkpoint genes and enhance chemotherapy sensitivity to cisplatin, docetaxel, and gemcitabine. CONCLUSION: We established a novel scoring system to predict the prognosis and immune landscape of HNSCC patients. This signature exhibits satisfactory predictive effects and the potential to guide comprehensive treatment for patients.

Expression profile and prognostic value of CXCR family members in head and neck squamous cell carcinoma.

BACKGROUND: CXC chemokine receptor gene family consists of seven well-established members which are broadly involved in biological functions of various cancers. Currently, limited studies have shed light on the expression profile of CXCR family members (CXCRs), as well as their prognostic value, in head and neck squamous cells carcinoma (HNSCC). METHODS: The data for this study were retrieved from the Cancer Genome Atlas database and other publicly available databases, including gene expression, methylation profiles, clinical information, immunological features, and prognoses. The expression pattern and prognostic values of CXCRs were identified, and the potential mechanism underlying CXCRs function in HNSCC was investigated by gene set enrichment analysis (GSEA). RESULTS: CXCRs were differentially expressed in HNSCC. As shown by Kaplan-Meier analysis, high CXCR3-6 expression was significantly associated with better prognostic outcomes of HNSCC patients, including overall survival and progression-free survival. According to the results of univariate and multivariate Cox proportional risk regression analysis, it was demonstrated that upregulation of CXCR3-6 was an independent factor for better prognosis, while the two other clinical features, age and stage, were factors for worse prognosis. A significant positive correlation between CXCR3-6 and tumor-infiltrated immune cells was revealed by results from Tumor Immune Estimation Resource and CIBERSORT analysis database. The main involvement of CXCRs in immune and inflammatory responses was further confirmed by GSEA. CONCLUSIONS: Overall, this study provided a rationale for targeting CXCRs as a promising therapeutic strategy of HNSCC.

Arylsulfatase I is a prognostic biomarker for head and neck squamous cell carcinoma and Pan-cancer.

BACKGROUND: Sulfatase gene family members mediate various biological functions in tumor stroma and tumor cell environments. However, the expressions and prognostic value of Arylsulfatase I (ARSI), a sulfatase gene family member, in head and neck squamous cell carcinoma (HNSC) have not been fully established. METHODS: Arylsulfatase I expressions in pan-cancer were profiled using publicly available databases. Then, univariate Cox regression, Kaplan-Meier, and the Pearson's correlation analyses were performed to determine correlations between ARSI expressions and cancer prognosis, immune cell status, and drug sensitivity. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were used to assess the potential mechanisms underlying ARSI functions in HNSC. RESULTS: Arylsulfatase I was highly expressed in 15 cancer types, with significant expressions in HNSC. Elevated ARSI levels were associated with worse prognostic outcomes in HNSC patients. In addition, GSVA and GSEA showed that ARSI was highly involved in tumor cell escape and inflammatory responses. Expressions of ARSI negatively correlated with tumor mutation burden or microsatellite instability and positively correlated with immune-related genes. Elevated ARSI expressions conferred poor tolerance to daporinad and sinularin, but increased cell sensitivity to dasatinib and XAV939. CONCLUSION: Arylsulfatase I is a promising prognostic and therapeutic target for HNSC.

Identification of several senescence-associated genes signature in head and neck squamous cell carcinoma.

BACKGROUND: As one of the core aging processes, cellular senescence is associated with tumorigenesis, growth, and immune modulation in cancers. Nevertheless, the prognosis of senescence-associated genes (SAGs) signature in head and neck squamous cell carcinoma (HNSCC) remains to be further evaluated. METHODS: The transcriptome and corresponding clinical datasets of SAGs in patients with HNSCC were downloaded from public databases. A new prognostic SAGs signature was established with least absolute shrinkage and selection operator discussion. Patients with HNSCC were fallen into two risk groups based on each sample's risk mark and the cutoff point. The survival analysis was extended to determine the predictive accuracy of the SAGs signature. Furthermore, the evaluation of SAGs signature was made according to clinicopathological characteristics, survival state, the infiltration of inflammatory cells, and efficacy of immunotherapy. RESULTS: 41 SAGs were recognized and adopted to establish the forecast signature. The survival analysis indicated that patients with HNSCC in the high-senescent score group had significantly reduced overall survival compared with those in the low-senescent score group. It was certified that the risk score of SAGs signature was a separate predicting agent for HNSCC applying Cox regression analysis. According to functional analysis, some immune-associated pathways were increased in the low-senescent score group significantly. High-senescent score group was correlated with poor clinicopathological characteristics, given less the infiltration of inflammatory cells state and worse immunotherapeutic effect. CONCLUSION: A new SAG signature predicting result and response to immunotherapy of HNSCC was identified. Cellular senescence may be a hidden target for HNSCC.

A 5'-tiRNA fragment that inhibits proliferation and migration of laryngeal squamous cell carcinoma by targeting PIK3CD.

tRNA-derived small RNAs (tsRNAs) participate in several biological processes, including carcinogenesis. The correlations between tsRNAs and human cancers are attracting substantial attention. Nevertheless, the involvement of tsRNAs in laryngeal squamous cell carcinoma (LSCC) progression remains unclear. We constructed tsRNAs expression profiles in LSCC and adjacent normal tissues by next-generation sequencing. Interestingly, we identified a specific 5'-tiRNA fragment (tRF-33-Q1Q89P9L842205) that was significantly downregulated and was closely associated with lymph node metastasis and advanced stages of LSCC. Importantly, we found that tRF-33-Q1Q89P9L842205 suppressed cell growth, proliferation, migration, invasion and induced apoptosis in LSCC by directly silencing phosphoinositide 3-kinase catalytic subunit (PIK3CD). We speculated that tRF-33-Q1Q89P9L842205 is a potential diagnostic biomarker for LSCC and acts as a tumor suppressor by directly targeting PIK3CD.

CD3D: a prognostic biomarker associated with immune infiltration and immunotherapeutic response in head and neck squamous cell carcinoma.

Recent studies have demonstrated that CD3D activates T-cell-related signal transduction and is associated with the antitumor immune response in several cancers. This study explored the role of CD3D in head and neck squamous cell carcinoma (HNSCC). A total of 499 HNSCC tissues and 44 normal controls were acquired from The Cancer Genome Atlas as the training cohort. GSE65858 included 270 HNSCC patients and was obtained from the Gene Expression Omnibus database as the test cohort. Overall, 172 HNSCC patients were collected as the validation cohort. CD3D expression in the validation cohort was measured by quantitative real-time polymerase chain reaction. The Kaplan-Meier plot revealed that high CD3D expression was associated with longer overall survival in HNSCC patients. Univariate and multivariate analyses showed that CD3D expression was an independent prognostic factor for HNSCC patients, which was confirmed in the test cohort and validation cohort. Furthermore, GO, KEGG, and GSEA analyses revealed the association of CD3D with immune-related pathways. Subsequently, ESTIMATE analysis showed the association between CD3D and the tumor microenvironment, while ssGSEA showed a remarkable positive link between CD3D and immune-related functions. Multiple algorithms demonstrated that high CD3D expression was associated with more immune effector cell infiltration. Finally, the tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) showed that patients with high CD3D could benefit from immunotherapy. In summary, CD3D was an independent favorable prognostic biomarker and correlated with immune cell infiltration and immune-related function, as well as an efficient indicator of immunotherapy response for HNSCC patients.

Identification of immune-related lncRNA panel for predicting immune checkpoint blockade and prognosis in head and neck squamous cell carcinoma.

PURPOSE: Immunotherapy is changing head and neck squamous cell carcinoma (HNSCC) treatment pattern. According to the Chinese Society of Clinical Oncology (CSCO) guidelines, immunotherapy has been deemed as first-line recommendation for recurrent/metastatic HNSCC, marking that advanced HNSCC has officially entered the era of immunotherapy. Long non-coding RNAs (lncRNAs) impact every step of cancer immunity. Therefore, reliable immune-lncRNAs able to accurately predict the immune landscape and survival of HNSCC are crucial to clinical management. METHODS: In the current study, we downloaded the transcriptomic and clinical data of HNSCC from The Cancer Genome Atlas and identified differentially expressed immune-related lncRNAs (DEir-lncRNAs). Further then, Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to identify proper DEir-lncRNAs to construct optimal risk model. Low-risk and high-risk groups were classified based on the optimal cut-off value generated by the areas under curve for receiver operating characteristic curves (AUC), and Kaplan-Meier survival curves were utilized to validate the prediction model. We then evaluated the model based on the clinical factors, immune cell infiltration, and chemotherapeutic and immunotherapeutic efficacy between two groups. RESULTS: In our study, we identified 256 Deir-lncRNAs in HNSCC. A total of 18 Deir-lncRNA pairs (consisting of 35 Deir-lncRNAs) were used to construct a risk model significantly associated with survival of HNSCC. Cox proportional hazard regression analysis confirmed that our risk model could be served as an independent prognostic indicator. Besides, HNSCC patients with low-risk score significantly enriched of CD8+ T cell, and corelated with high chemosensitivity and immunotherapeutic sensitivity. CONCLUSION: Our risk model could be served as a promising clinical prediction indicator, effective discoursing of the immune cell infiltration of HNSCC patients, and distinguishing patients who could benefit from chemotherapy and immunotherapy.

A novel Pyroptosis-related long non-coding RNA signature for predicting the prognosis and immune landscape of head and neck squamous cell carcinoma.

BACKGROUND: Pyroptosis plays an essential function in carcinogenesis and the antitumor immune response. Herein, we constructed a pyroptosis-related long noncoding RNA (prLncRNA) signature to predict therapeutic effects and outcomes for head and neck squamous cell carcinoma (HNSCC) patients. METHODS: Patients obtained from the TCGA-HNSC project were divided randomly into the training as well as the validation sets at a ratio of 7:3. A novel prognostic prLncRNA signature was constructed from the results of the training set using the least absolute shrinkage and selection operation. The medium value was used as the basis for categorizing all HNSCC patients into a low- or high-risk cohort. Cox regression and Kaplan-Meier (KM) survival analyses were executed to estimate the prognostic value. We also evaluated the functional enrichment, tumor microenvironment, immune cell infiltration, and the sensitivity to chemotherapy and immunotherapy between the high- and low-risk cohorts. RESULTS: Nineteen prognostic prlncRNAs were identified to establish the prognostic signature. Multivariate Cox regression and KM survival analyses confirmed that this prlncRNA signature might serve as an independent prognostic indicator of patient survival, which was subsequently confirmed using a validating dataset. Multiple ROC curves indicated the prlncRNA signature presented a more predictive power than clinicopathological factors (age, sex, tumor grade, and tumor stage). GO, KEGG, and GSEA enrichment analysis disclosed several immune-related pathways which appeared to be enhanced in the low-risk cohort. ESTIMATE, CIBERSORT, and ssGSEA algorithms indicated considerable differences in the tumor microenvironment and immune cell infiltration in the low- and high-risk cohorts. Furthermore, the low-risk cohort was predicted to achieve a better response to immunotherapeutic drugs, while in contrast, the high-risk cohort would be more sensitive to chemotherapy drugs. CONCLUSIONS: Our findings robustly demonstrate that our constructed prlncRNA signature could serve as an efficient indicator of prognosis, immunotherapy response, and chemosensitivity for HNSCC patients.

Construction of a necroptosis-related lncRNA signature to predict the prognosis and immune microenvironment of head and neck squamous cell carcinoma.

BACKGROUND: Previous studies have determined that necroptosis-related genes are potential biomarkers in head and neck squamous cell carcinoma (HNSCC). Herein, we established a novel risk model based on necroptosis-related lncRNAs (nrlncRNAs) to predict the prognosis of HNSCC patients. METHODS: Transcriptome and related information were obtained from TCGA database, and an nrlncRNA signature was established based on univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model, and a nomogram for survival prediction was established. Gene set enrichment analysis, immune analysis, drug sensitivity analysis, correlation with N6-methylandenosin (m6A), and tumor stemness analysis were performed. Furthermore, the entire set was divided into two clusters for further discussion. RESULTS: A novel signature was established with six nrlncRNAs. The areas under the ROC curves (AUCs) for 1-, 3-, and 5-year overall survival (OS) were 0.699, 0.686, and 0.645, respectively. Patients in low-risk group and cluster 2 had a better prognosis, more immune cell infiltration, higher immune function activity, and higher immune scores; however, patients in high-risk group and cluster 1 were more sensitive to chemotherapy. Moreover, the risk score had negative correlation with m6A-related gene expression and tumor stemness. CONCLUSION: According to this study, we constructed a novel signature with nrlncRNA pairs to predict the survival of HNSCC patients and guide immunotherapy and chemotherapy. This may possibly promote the development of individualized and precise treatment for HNSCC patients.

Construction of an algorithm based on oncosis-related LncRNAs comprising the molecular subtypes and a risk assessment model in lung adenocarcinoma.

BACKGROUND: As an important non-apoptotic cell death method, oncosis has been reported to be closely associated with tumors in recent years. However, few research reported the relationship between oncosis and lung cancer. METHODS: In this study, we established an oncosis-based algorithm comprised of cluster grouping and a risk assessment model to predict the survival outcomes and related tumor immunity of patients with lung adenocarcinomas (LUAD). We selected 11 oncosis-related lncRNAs associated with the prognosis (CARD8-AS1, LINC00941, LINC01137, LINC01116, AC010980.2, LINC00324, AL365203.2, AL606489.1, AC004687.1, HLA-DQB1-AS1, and AL590226.1) to divide the LUAD patients into different clusters and different risk groups. Compared with patients in clsuter1, patients in cluster2 had a survival advantage and had a relatively more active tumor immunity. Subsequently, we constructed a risk assessment model to distinguish between patients into different risk groups, in which low-risk patients tend to have a better prognosis. GO enrichment analysis revealed that the risk assessment model was closely related to immune activities. In addition, low-risk patients tended to have a higher content of immune cells and stromal cells in tumor microenvironment, higher expression of PD-1, CTLA-4, HAVCR2, and were more sensitive to immune checkpoint inhibitors (ICIs), including PD-1/CTLA-4 inhibitors. The risk score had a significantly positive correlation with tumor mutation burden (TMB). The survival curve of the novel oncosis-based algorithm suggested that low-risk patients in cluster2 have the most obvious survival advantage. CONCLUSION: The novel oncosis-based algorithm investigated the prognosis and the related tumor immunity of patients with LUAD, which could provide theoretical support for customized individual treatment for LUAD patients.